南京工业大学学报（自然科学版）2011，Vol.33Issue(6)：72-76,5.DOI:10.3969/j.issn.1671-7627.2011.06.015
基于改进聚类算法的RBF网络及其应用
Improved clustering method based RBF network and its application
摘要
Abstract
Radial basis function ( RBF) network was used to approximate any continuous nonlinear function and was widely applied in process modeling and prediction due to its good performance and fast training. An important factor of affecting the performance of RBF network was the selection of the Gaussian centers. An improved k-means clustering algorithm was developed to determine the optimal cluster number automatically and make the final cluster centers distribute appropriately. When the algorithm was applied to RBF network, the significant performance could be achieved with much smaller network compared with usual clustering method. Simulation and practical results showed the effectiveness of the algorithm.关键词
k-means聚类/RBF网络/建模Key words
k-means clustering/RBF network/modeling分类
信息技术与安全科学引用本文复制引用
李春富,郑小青,葛铭..基于改进聚类算法的RBF网络及其应用[J].南京工业大学学报（自然科学版）,2011,33(6):72-76,5.基金项目
浙江省科技计划资助项目(2009C31161) （2009C31161）
